When Data Overload Can Make You Slower
A couple of weeks ago I spoke at the Sport Performance Data and Fan Engagement Summit in San Francisco.
The Performance side of the summit covered just about every aspect of how to collect and use data to improve athletic performance. There were presenters from team sports, individual sports, college and professional sports. It was interesting to hear how other sports are finally catching up with how we’ve used metrics for years in endurance. But what really caught my attention was the overwhelming number of experts explaining why metrics do not always translate into better performances. They universally agreed that there is a point when data overload can make you slower. Here’s how they explained it.
Data is great for helping athlete’s gain awareness between what they are experiencing and what is going on physically and biomechanically.
“Hard” is a relative number. So is “easy”. “Moderate” has an even broader meaning to athletes. So in terms of measuring intensity, metrics are great to have. It quantifies different intensity levels and relates that to how athletes are feeling at those levels. This is especially good for beginners who have nothing to gauge what they should be experiencing in their training.
Data paints a picture of how they are moving through the range of motion of their sport.
It’s one thing to tell someone their cadence rate is too low. It’s another to have a number that changes as they gain the skill to improve it. Again this is best for those just starting out in a sport to help them understand how all your parts are working together and then doing what it takes to become more efficient at it.
What started to have the mixed bag is when data overload made someone slower. Take a look at tracking sleep. Certainly good quality sleep and getting enough of it is needed to optimize athletic performance. Some athletes measuring their sleep did get more better quality by using a tracker. It became their conscience to get them to bed earlier. They saw what habits before bed led to better sleep rather than a worse night in bed.
But not everyone got better sleep who tracked it.
Some got “performance anxiety” when it came to getting good quality sleep during shuteye. They got so worried about getting enough good sleep that they actually ended up spending a lot less time in the most important deep restful states.
The same negative was seen from collecting a lot of training data from athletes. When it came in below expectations, some athletes took it as a personal slap in the face rather than just info to stick in the back of their minds and use over the long haul. These were the people who were hoping to always show good numbers. They hoped to post data that was a little bit better than the day before. It became completely demoralizing for them when those goals weren’t met. A session with lousy numbers brought on a lousy attitude going forward.
If you are a veteran of data you likely know how to take it as just that, as data. You don’t let it overload you or define your life.
When your expectations don’t match what your device is showing from a training session, you take it the same way you would as a race that fell short. You’d figure out what might need to change going forward rather than letting it stall your progress by mulling it over endlessly.
If you are just starting out in a sport, use data as super potent feedback to accelerate your learning curve.
Use the numbers about cadence rate, speed, heart rate and power to help you correlate that with what is going on in your body. Take it and learn what that info is teaching you about how to hit the goals of each workout.
If your self-worth is living or dying based on your data, use it sparingly!
That’s when data overload can make you slower. Your data should be something to help you live up to your goals and expectations. If your overarching attitude is defined by it, then data is overload. If one day’s measures show a drop in value that takes you away from a positive outlook on the future, use it more like someone who is trying to lose weight would use a scale. Use those numbers periodically, not methodically every moment of your life.
I loved data. But then I was good at managing it.
My main metric was heart rate. I compared it to pace and speed. If I was getting faster at any given heart rate, that data showed that without a doubt my fitness was going up. But I also didn’t expect to see that happening in every session. Improvement is so very slow on a cellular human level. I was only able to measure those gains over long periods of time. No one’s body sets a personal best every day of the week!
On top of that, there are the natural ups and downs. Some days I was on. Some I was tired and off. I used data trends over weeks not workout to workout to get a clear picture of what was happening. That evened out the normal rhythms we all have. It helped me avoid data overload that would have made me slower. I used it to make me faster!
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